Construction of stochastic models for human thermal homeostasis

A construction of mathematical models for human thermal homeostasis is considered with the purpose of their subsequent parameter fitting to experimental data using adaptive Kalman filtering technique and solution of two main problems, such as parameter identification and fastest detection of the system changes. Averaged charts of daily temperature variations of bodies of the healthy adults are taken as a benchmark data. While constructing the models, stochastic origin of measurement error as well as many external factors of average daily temperature variations are taken into account. The deterministic models for human thermal homeostasis in case of continuous time are constructed. Then a stochastic component is entered into these models and, finally, the transition to discrete time is performed.